RISK AVERSION AND MOTOR INSURANCE DEMAND: EMPIRICAL EVIDENCE FROM NIGERIA
Insurance demand is often pushed by high level aversion of risk. Risk aversion is seen as the heartbeat of the demand for insurance. Therefore, this study examined the relationships between risk aversion and insurance demand with its empirical findings among selected motorists in Lagos, Nigeria. Thi...
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Veröffentlicht in: | Analele Universitatii din Craiova. Seria stiinte economice 2019-12, Vol.2 (47), p.211-222 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | Insurance demand is often pushed by high level aversion of risk. Risk aversion is seen as the heartbeat of the demand for insurance. Therefore, this study examined the relationships between risk aversion and insurance demand with its empirical findings among selected motorists in Lagos, Nigeria. This study adopted descriptive research plan. While convenience sampling procedure, information was gathered via a structured questionnaire. With 10 selected Local Government Council Areas in Lagos State, five hundred and fourteen (514) respondents were targeted. This research adopted simple frequency technique and Kendall’s rank correlation coefficient. While some germane questions were formulated and to which supportive discussion were verbally validated, an hypothetical statement was tested. The study recommended that more clarifications be made by insurance firms in dealing properly with motor insurance policyholders in relations to their diverse risk attitudes; motorists’ decreasing marginal utility of income should concurrently be matched with their decision to opt for motor insurance policies; insurance companies should design insurance products that are inherently concave utility driven in nature so as to change the usual maxim that ‘insurance is sold but not bought’ to ‘insurance is bought and sold’; and Government should drive a policy to combat poor risk attitude among motorists and ensure that motor insurance is applied as a requisite instrument for moderating behaviours among drivers. |
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ISSN: | 1223-365X 1843-3723 |